PNNL

Abstract

Soil respiration (Rs, the soil surface-to-atmosphere CO2 flux) has been measured in the field for decades, but only recently have we begun to assemble and leverage these small-scale but extensive data. Recently, Zhao et al. (2017) applied a novel artificial neural network model to the problem of estimating the global Rs flux and understanding its variations between regions and biomes. Their results point to a convergence in estimates of global Rs, and raise interesting questions about the Rs response to climate change, the availability of data to support such approaches, and possibility for further leveraging the long record of observed Rs in global ecosystems.